Pavement Health Monitoring System Based on an Embedded Sensing Network

As one of the most important and expensive investments/assets in modern society, asphalt concrete pavements age and deteriorate with time as a result of asphalt mixture aging, cumulative loading, environmental conditions, and/or inadequate maintenance. The detection of pavement health condition is very important for a pavement analysis and management system. In this paper, a pavement health monitoring system was developed based on an embedded sensing network with an efficient combination of various commercial pavement sensors. The collected pavement responses were clear and reasonable and compared with a numerical simulation. The modulus of the pavement surface layer can be back-calculated every year or every several months based on testing runs and numerical models. Fatigue cracking and rutting models were selected to predict the distress of the experimental section according to the actual strain measurement from each passing vehicle. A health monitoring system, which contains the continuous monitoring and periodic testing as routines, is proposed as an important component of a pavement management system.

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